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Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease-causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome-wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution.

Original publication

DOI

10.1002/humu.22818

Type

Journal article

Journal

Hum Mutat

Publication Date

09/2015

Volume

36

Pages

823 - 830

Keywords

autozygosity mapping, exome, next generation sequencing, software, Chromosome Mapping, Computational Biology, Consanguinity, Exome, Genetic Association Studies, Genetic Variation, Genotype, High-Throughput Nucleotide Sequencing, Humans, Inheritance Patterns, Pedigree, Polymorphism, Single Nucleotide, Software